Using event-related brain potentials to evaluate motor-auditory latencies in virtual reality.

Actions in the real world have immediate sensory consequences. Mimicking these in digital environments is within reach, but technical constraints usually impose a certain latency (delay) between user actions and system responses. It is important to assess the impact of this latency on the users, ideally with measurement techniques that do not interfere with their digital experience.

Anticipatory information makes the difference: Behavioral effects and user assessments of a cyclist warning system to enhance cyclists' situation awareness.

Problem: Increasing numbers of crashes involving pedelecs, and particularly older pedelec users, induce a need to enhance cycling safety. We evaluated a prototype cyclist warning system (CWS) that aims to increase situation awareness (SA) by alerting to safety critical events (SCE) with trimodal (auditory, visual, tactile).

Method: To investigate the effects of CWS usage, we conducted a 2x2 mixed design bicycle simulator study with factors (1) CWS usage (within: rides WITH vs.

Assessing mental workload with wearable devices - Reliability and applicability of heart rate and motion measurements.

Wearable devices are increasingly used for assessing physiological data. Industry 4.0 aims to achieve the real-time assessment of the workers' condition to adapt processes including the current mental workload.

The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians' Trust and Acceptance of Automated Vehicle Communication Signals.

To ensure traffic flow and road safety in automated driving, external human-machine interfaces (eHMIs) could prospectively support the interaction between automated vehicles (AVs; SAE Level 3 or higher) and pedestrians if implicit communication is insufficient. Particularly elderly pedestrians (≥65 years) who are notably vulnerable in terms of traffic safety might benefit of the advantages of additional signals provided by eHMIs. Previous research showed that eHMIs were assessed as useful means of communication in AVs and were preferred over exclusively implicit communication signals.

The box task - a method for assessing in-vehicle system demand.

The use of advanced in-vehicle information systems (IVIS) and other complex devices such as smartphones while driving can lead to driver distraction, which, in turn, increases safety-critical event risk. Therefore, using methods for measuring driver distraction caused by IVIS is crucial when developing new in-vehicle systems. In this paper, we present the setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) as a tool to assess visual-manual and cognitive distraction effects.

Information stored in memory affects abductive reasoning.

Abductive reasoning describes the process of deriving an explanation from given observations. The theory of abductive reasoning (TAR; Johnson and Krems, Cognitive Science 25:903-939, 2001) assumes that when information is presented sequentially, new information is integrated into a mental representation, a situation model, the central data structure on which all reasoning processes are based. Because working memory capacity is limited, the question arises how reasoning might change with the amount of information that has to be processed in memory.

Memory-related cognitive load effects in an interrupted learning task: A model-based explanation.

Background: The Cognitive Load Theory provides a well-established framework for investigating aspects of learning situations that demand learners' working memory resources. However, the interplay of these aspects at the cognitive and neural level is still not fully understood.

Method: We developed four computational models in the cognitive architecture ACT-R to clarify underlying memory-related strategies and mechanisms.

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop.

Objective: We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs).

Background: As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception.

Measuring driver distraction - Evaluation of the box task method as a tool for assessing in-vehicle system demand.

Several tools have been developed over the past twenty years to assess the degree of driver distraction caused by secondary task engagement. A relatively new and promising method in this area is the box task combined with a detection response task (BT + DRT). However, no evaluation regarding the BT's sensitivity currently exists.

Using European naturalistic driving data to assess secondary task engagement when stopped at a red light.

Problem: Some evidence exists that drivers choose to engage in secondary tasks when the driving demand is low (e.g., when the car is stopped).

Tracing current explanations in memory: A process analysis based on eye-tracking.

Sequential abductive reasoning is the process of finding the best explanation for a set of observations. Explanations can be multicausal and require the retrieval of previously found ones from memory. The theory of abductive reasoning (TAR) allows detailed predictions on what information is stored and retrieved from memory during reasoning.

Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction.

Objective: We observe the effects of in-vehicle system gesture-based interaction versus touch-based interaction on driver distraction and user experience.

Background: Driver distraction is a major problem for traffic safety, as it is a contributing factor to a number of accidents. Visual distraction in particular has a highly negative impact on the driver.

An experimental study to investigate design and assessment criteria: What is important for communication between pedestrians and automated vehicles?

In the near future, more vehicles will have automated functions. The traffic system will be a shared space of automated and manually driven vehicles. In our study we focused on the perspective of vulnerable road users, namely pedestrians, in cooperative situations with automated vehicles.

Regenerative braking failures in battery electric vehicles and their impact on the driver.

A unique feature of battery electric vehicles (BEV) is their regenerative braking system (RBS) to recapture kinetic energy in deceleration maneuvers. If such a system is triggered via gas pedal, most deceleration maneuvers can be executed by just using this pedal. This impacts the driving task as different deceleration strategies can be applied.

Driving comfort, enjoyment and acceptance of automated driving - effects of drivers' age and driving style familiarity.

Automated driving has the potential to improve the safety and efficiency of future traffic and to extend elderly peoples' driving life, provided it is perceived as comfortable and joyful and is accepted by drivers. Driving comfort could be enhanced by familiar automated driving styles based on drivers' manual driving styles. In a two-stage driving simulator study, effects of driving automation and driving style familiarity on driving comfort, enjoyment and system acceptance were examined.

Covert shifts of attention can account for the functional role of "eye movements to nothing".

When trying to remember verbal information from memory, people look at spatial locations that have been associated with visual stimuli during encoding, even when the visual stimuli are no longer present. It has been shown that such "eye movements to nothing" can influence retrieval performance for verbal information, but the mechanism underlying this functional relationship is unclear. More precisely, covert in comparison to overt shifts of attention could be sufficient to elicit the observed differences in retrieval performance.

Using SHRP 2 naturalistic driving data to assess drivers' speed choice while being engaged in different secondary tasks.

Introduction: The engagement in secondary tasks while driving has been found to result in considerable impairments of driving performance. Texting has especially been suspected to be associated with an increased crash risk. At the same time, there is evidence that drivers use various self-regulating strategies to compensate for the increased demands caused by secondary task engagement.

Does this range suit me? Range satisfaction of battery electric vehicle users.

User satisfaction is a vital design criterion for sustainable systems. The present research aimed to understand factors relating to individually perceived range satisfaction of battery electric vehicle (BEV) users. Data from a large-scale BEV field trial (N = 72) were analyzed.

Watching diagnoses develop: Eye movements reveal symptom processing during diagnostic reasoning.

Finding a probable explanation for observed symptoms is a highly complex task that draws on information retrieval from memory. Recent research suggests that observed symptoms are interpreted in a way that maximizes coherence for a single likely explanation. This becomes particularly clear if symptom sequences support more than one explanation.

Can We Study Autonomous Driving Comfort in Moving-Base Driving Simulators? A Validation Study.

Objective: To lay the basis of studying autonomous driving comfort using driving simulators, we assessed the behavioral validity of two moving-base simulator configurations by contrasting them with a test-track setting.

Background: With increasing level of automation, driving comfort becomes increasingly important. Simulators provide a safe environment to study perceived comfort in autonomous driving.

Prior Familiarization With Takeover Requests Affects Drivers' Takeover Performance and Automation Trust.

Objective: The objective for this study was to investigate the effects of prior familiarization with takeover requests (TORs) during conditional automated driving on drivers' initial takeover performance and automation trust.

Background: System-initiated TORs are one of the biggest concerns for conditional automated driving and have been studied extensively in the past. Most, but not all, of these studies have included training sessions to familiarize participants with TORs.

The influence of speed, cyclists' age, pedaling frequency, and observer age on observers' time to arrival judgments of approaching bicycles and e-bikes.

Given their potential to reach higher speed levels than conventional bicycles, the growing market share of e-bikes has been the reason for increased concerns regarding road safety. Previous studies have shown a clear relationship between object approach speed and an observers' judgment of when the object would reach a predefined position (i.e.

The diversity effect in diagnostic reasoning.

Diagnostic reasoning draws on knowledge about effects and their potential causes. The causal-diversity effect in diagnostic reasoning normatively depends on the distribution of effects in causal structures, and thus, a psychological diversity effect could indicate whether causally structured knowledge is used in evaluating the probability of a diagnosis, if the effect were to covary with manipulations of causal structures. In four experiments, participants dealt with a quasi-medical scenario presenting symptom sets (effects) that consistently suggested a specified diagnosis (cause).

Keep Your Scanners Peeled: Gaze Behavior as a Measure of Automation Trust During Highly Automated Driving.

Objective: The feasibility of measuring drivers' automation trust via gaze behavior during highly automated driving was assessed with eye tracking and validated with self-reported automation trust in a driving simulator study.

Background: Earlier research from other domains indicates that drivers' automation trust might be inferred from gaze behavior, such as monitoring frequency.

Method: The gaze behavior and self-reported automation trust of 35 participants attending to a visually demanding non-driving-related task (NDRT) during highly automated driving was evaluated.

Which Factors Can Protect Against Range Stress in Everyday Usage of Battery Electric Vehicles? Toward Enhancing Sustainability of Electric Mobility Systems.

Objective: The objective of the present research was to advance understanding of factors that can protect against range anxiety, specifically range stress in everyday usage of battery electric vehicles (BEVs).

Background: Range anxiety is a major barrier to the broad adoption of sustainable electric mobility systems. To develop strategies aimed at overcoming range anxiety, a clear understanding of this phenomenon and influencing factors is needed.